An LLM-simulated immersive street-crossing system for autistic children showed improved engagement and faster safe-crossing decisions in a 14-participant study, but measurement and sample limitations temper the claim.
The Nexus of AR/VR, AI, UI/UX, and Robotics Technologies in Enhancing Learning and Social Interaction for Children with Autism Spectrum Disorders: A Systematic Review
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abstract
The emergence of large language models (LLMs), augmented reality (AR), and user interface/user experience (UI/UX) design in therapies for children, especially with disorders like autism spectrum disorder (ASD), is studied in detail in this review study. 150 publications were collected by a thorough literature search throughout PubMed, ACM, IEEE Xplore, Elsevier, and Google Scholar; 60 of them were chosen based on their methodological rigor and relevance to the focus area. Three of the primary areas are studied and covered in this review: how AR can improve social and learning results, how LLMs can support communication, and how UI/UX design affects how effective these technologies can be. Results show that while LLMs can provide individualized learning and communication support, AR has shown promise in enhancing social skills, motivation, and attention. For children with ASD, accessible and engaging interventions rely heavily on effective UI/UX design, but there is still a significant lack of robotics-based education and therapeutic programs specifically tailored for autistic children. To optimize the benefits of these technologies in ASD therapies and immersive education, the study emphasizes the need for additional research to address difficulties related to customization, accessibility, and integration.
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Designing LLM-simulated Immersive Spaces to Enhance Autistic Children's Social Affordances Understanding
An LLM-simulated immersive street-crossing system for autistic children showed improved engagement and faster safe-crossing decisions in a 14-participant study, but measurement and sample limitations temper the claim.